The role of CT in prognosis prediction in COVID-19 patients

Tonje Gravdal; Kine Storås; Albertina Rusandu; Ragna Stalsberg

doi:10.7577/radopen.6092

Authors

Tonje Gravdal Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU) https://orcid.org/0009-0009-8592-6139
Kine Storås Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU) https://orcid.org/0009-0005-9322-1957
Albertina Rusandu Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU) https://orcid.org/0000-0001-9784-6157
Ragna Stalsberg Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU) https://orcid.org/0000-0002-9611-1615

DOI:

https://doi.org/10.7577/radopen.6092

Keywords:

COVID-19, Prognosis prediction, Computed Tomography, Literature review

Abstract

Introduction: The aim of the present study was to summarize and evaluate previously published scientific studies examining whether computed tomography (CT) of the thorax can predict the COVID-19 prognosis. The purpose is to clarify whether CT can predict the COVID-19 prognosis, and also if a CT examination can predict whether the patient will be admitted to the intensive care unit (ICU) or not.

Method: Traditional digital literature searches were performed in the Medline, Pubmed and Embase databases. Subsequent back- and forward citation-based searches were then conducted. A total of 17 studies were included according to preset inclusion and exclusion criteria.

Results: All 17 included articles were retrospective studies. The mean number of patients included was 219 (range: 28-901). Overall, the studies showed that CT-findings of abnormalities in the lung tissue may provide a possible COVID-19 prognosis determination. A total of 11 studies used a quantitative scoring system to evaluate the lung images. Based on the percentage of lung involvement, the ICU patients had a higher score compared with patients not admitted to the ICU. The pathology type with the highest predictive value was crazy paving pattern followed by vascular enlargement and air bronchogram. Pleural effusion and pleural thickening can help estimating the prognosis according to some of the studies.

Conclusion: The present study shows that CT can contribute to early diagnosis and predict the prognosis when using scoring systems or qualitative assessment of certain radiologic features which are more prevalent in critically ill COVID-19 patients.

References

Liu Y-C, Kuo R-L, Shih S-R. COVID-19: The first documented coronavirus pandemic in history. Biomedical Journal 2020;43(4):328-333. DOI: 10.1016/j.bj.2020.04.007.

Majumder J, Minko T. Recent Developments on Therapeutic and Diagnostic Approaches for COVID-19. Aaps j 2021;23(1):14. (In eng). DOI: 10.1208/s12248-020-00532-2.

Koch V, Gruenewald LD, Albrecht MH, et al. Lung Opacity and Coronary Artery Calcium Score: A Combined Tool for Risk Stratification and Outcome Prediction in COVID-19 Patients. Acad Radiol 2022;29(6):861-870. (In eng). DOI: 10.1016/j.acra.2022.02.019.

Filchakova O, Dossym D, Ilyas A, Kuanysheva T, Abdizhamil A, Bukasov R. Review of COVID-19 testing and diagnostic methods. Talanta 2022;244:123409. (In eng). DOI: 10.1016/j.talanta.2022.123409.

Bernheim A, Mei X, Huang M, et al. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology 2020;295(3):685-691. DOI: 10.1148/radiol.2020200463.

Supino M, d’Onofrio A, Luongo F, Occhipinti G, Dal Co A. The effects of containment measures in the Italian outbreak of COVID-19. BMC Public Health 2020;20(1):1806. DOI: 10.1186/s12889-020-09913-w.

Fazzari F, Cozzi O, Maurina M, et al. In-hospital prognostic role of coronary atherosclerotic burden in COVID-19 patients. J Cardiovasc Med (Hagerstown) 2021;22(11):818-827. (In eng). DOI: 10.2459/jcm.0000000000001228.

Pediconi F, Rizzo V, Schiaffino S, et al. Visceral adipose tissue area predicts intensive care unit admission in COVID-19 patients. Obes Res Clin Pract 2021;15(1):89-92. (In eng). DOI: 10.1016/j.orcp.2020.12.002.

Bihan H, Heidar R, Beloeuvre A, et al. Epicardial adipose tissue and severe Coronavirus Disease 19. Cardiovasc Diabetol 2021;20(1):147. (In eng). DOI: 10.1186/s12933-021-01329-z.

Machnicki S, Patel D, Singh A, et al. The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19: A Review of Literature. Chest 2021;160(2):652-670. (In eng). DOI: 10.1016/j.chest.2021.04.004.

Garg M, Prabhakar N, Bhalla AS, et al. Computed tomography chest in COVID-19: When & why? Indian J Med Res 2021;153(1 & 2):86-92. (In eng). DOI: 10.4103/ijmr.IJMR_3669_20.

Chua F, Armstrong-James D, Desai SR, et al. The role of CT in case ascertainment and management of COVID-19 pneumonia in the UK: insights from high-incidence regions. Lancet Respir Med 2020;8(5):438-440. (In eng). DOI: 10.1016/s2213-2600(20)30132-6.

Hu X, Rousseau R, Chen J. On the definition of forward and backward citation generations. Journal of Informetrics 2011;5(1):27-36. DOI: 10.1016/j.joi.2010.07.004.

Jared C, Miloslav K, Sandrine D, et al. Chapter 9: Diagnostic test accuracy systematic reviews. JBI; 2019.

Angeli E, Dalto S, Marchese S, et al. Prognostic value of CT integrated with clinical and laboratory data during the first peak of the COVID-19 pandemic in Northern Italy: A nomogram to predict unfavorable outcome. Eur J Radiol 2021;137:109612. (In eng). DOI: 10.1016/j.ejrad.2021.109612.

Colombi D, Bodini FC, Petrini M, et al. Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia. Radiology 2020;296(2):E86-e96. (In eng). DOI: 10.1148/radiol.2020201433.

Leonardi A, Scipione R, Alfieri G, et al. Role of computed tomography in predicting critical disease in patients with covid-19 pneumonia: A retrospective study using a semiautomatic quantitative method. Eur J Radiol 2020;130:109202. (In eng). DOI: 10.1016/j.ejrad.2020.109202.

Salaffi F, Carotti M, Tardella M, et al. The role of a chest computed tomography severity score in coronavirus disease 2019 pneumonia. Medicine (Baltimore) 2020;99(42):e22433. (In eng). DOI: 10.1097/md.0000000000022433.

Baysal B, Dogan MB, Gulbay M, et al. Predictive performance of CT for adverse outcomes among COVID-19 suspected patients: a two-center retrospective study. Bosn J Basic Med Sci 2021;21(6):739-745. (In eng). DOI: 10.17305/bjbms.2020.5466.

Pence MC, Avdan Aslan A, Tunccan OG, Erbas G. Prognostic value of semi-quantitative CT-based score integrated with cardiovascular risk factors during the first peak of the COVID-19 pandemic: A new score to predict poor outcome. Eur J Radiol 2022;150:110238. (In eng). DOI: 10.1016/j.ejrad.2022.110238.

Tekcan Sanli DE, Yildirim D, Sanli AN, et al. Predictive value of CT imaging findings in COVID-19 pneumonia at the time of first-screen regarding the need for hospitalization or intensive care unit. Diagn Interv Radiol 2021;27(5):599-606. (In eng). DOI: 10.5152/dir.2020.20421.

Aminzadeh B, Layegh P, Foroughian M, et al. Evaluation of the Prognostic Value of Chest Computed Tomography Scan in COVID-19 Patients. Iranian Journal of Radiology 2021.

Hajiahmadi S, Shayganfar A, Janghorbani M, et al. Chest Computed Tomography Severity Score to Predict Adverse Outcomes of Patients with COVID-19. Infect Chemother 2021;53(2):308-318. DOI: 10.3947/ic.2021.0024.

Tabatabaei SMH, Talari H, Moghaddas F, Rajebi H. CT Features and Short-term Prognosis of COVID-19 Pneumonia: A Single-Center Study from Kashan, Iran. Radiol Cardiothorac Imaging 2020;2(2):e200130. (In eng). DOI: 10.1148/ryct.2020200130.

Büttner L, Aigner A, Fleckenstein FN, et al. Diagnostic Value of Initial Chest CT Findings for the Need of ICU Treatment/Intubation in Patients with COVID-19. Diagnostics (Basel) 2020;10(11) (In eng). DOI: 10.3390/diagnostics10110929.

Hosse C, Büttner L, Fleckenstein FN, et al. CT-Based Risk Stratification for Intensive Care Need and Survival in COVID-19 Patients-A Simple Solution. Diagnostics (Basel). 2021 Sep 4;11(9):1616. DOI: 10.3390/diagnostics11091616

Rorat M, Jurek T, Simon K, Guziński M. Value of quantitative analysis in lung computed tomography in patients severely ill with COVID-19. PLoS One 2021;16(5):e0251946. (In eng). DOI: 10.1371/journal.pone.0251946.

Yamada D, Ohde S, Imai R, Ikejima K, Matsusako M, Kurihara Y. Visual classification of three computed tomography lung patterns to predict prognosis of COVID-19: a retrospective study. BMC Pulm Med 2022;22(1):1. (In eng). DOI: 10.1186/s12890-021-01813-y.

Sun D, Li X, Guo D, et al. CT Quantitative Analysis and Its Relationship with Clinical Features for Assessing the Severity of Patients with COVID-19. Korean J Radiol 2020;21(7):859-868. (In eng). DOI: 10.3348/kjr.2020.0293.

Parry AH, Wani AH, Shah NN, Yaseen M, Jehangir M. Chest CT features of coronavirus disease-19 (COVID-19) pneumonia: which findings on initial CT can predict an adverse short-term outcome? BJR Open 2020;2(1):20200016. (In eng). DOI: 10.1259/bjro.20200016.

Nair AV, Kumar D, Yadav SK, Nepal P, Jacob B, Al-Heidous M. Utility of visual coronary artery calcification on non-cardiac gated thoracic CT in predicting clinical severity and outcome in COVID-19. Clin Imaging 2021;74:123-130. (In eng). DOI: 10.1016/j.clinimag.2021.01.015.

Almasi Nokiani A, Shahnazari R, Abbasi MA, Divsalar F, Bayazidi M, Sadatnaseri A. CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods. 2022;53(1) (In eng). DOI: 10.1186/s43055-022-00781-5.

Kwee TC, Kwee RM. Chest CT in COVID-19: What the Radiologist Needs to Know. RadioGraphics 2020;40(7):1848-1865. DOI: 10.1148/rg.2020200159.

Laino ME, Ammirabile A, Lofino L, et al. Prognostic findings for ICU admission in patients with COVID-19 pneumonia: baseline and follow-up chest CT and the added value of artificial intelligence. Emerg Radiol 2022;29(2):243-262. (In eng). DOI: 10.1007/s10140-021-02008-y.

Ojha V, Mani A, Pandey NN, Sharma S, Kumar S. CT in coronavirus disease 2019 (COVID-19): a systematic review of chest CT findings in 4410 adult patients. European Radiology 2020;30(11):6129-6138. DOI: 10.1007/s00330-020-06975-7.